Wan Luping, Jiang Yin, Zhu Xianggao, Wu Hao, Zhao Wei
School of Physics, Beihang University, Beijing, China.
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China.
Med Phys. 2023 Oct;50(10):6479-6489. doi: 10.1002/mp.16710. Epub 2023 Sep 11.
Adaptive radiotherapy (ART) can incorporate anatomical variations in a reoptimized treatment plan for fractionated radiotherapy. An automatic solution to objectively determine whether ART should be performed immediately after the daily image acquisition is highly desirable.
We investigate a quantitative criterion for whether ART should be performed in prostate cancer radiotherapy by synthesizing pseudo-CT (sCT) images and evaluating dosimetric impact on treatment planning using deep learning approaches.
Planning CT (pCT) and daily cone-beam CT (CBCT) data sets of 74 patients are used to train (60 patients) and evaluate (14 patients) a cycle adversarial generative network (CycleGAN) that performs the task of synthesizing high-quality sCT from daily CBCT. Automatic delineation (AD) of the bladder is performed on the sCT using the U-net. The combination of sCT and AD allows us to perform dose calculations based on the up-to-date bladder anatomy to determine whether the original treatment plan (ori-plan) is still applicable. For positive cases that the patients' anatomical changes and the associated dose calculations warrant re-planning, we made rapid plan revisions (re-plan) based on the ori-plan.
The mean absolute error within the region-of-interests (i.e., body, bladder, fat, muscle) between the sCT and pCT are 41.2, 25.1, 26.5, and 29.0HU, respectively. Taking the calculated results of pCT doses as the standard, for PTV, the gamma passing rates of sCT doses at 1 mm/1%, 2 mm/2% are 87.92%, 98.78%, respectively. The Dice coefficients of the AD-contours are 0.93 on pCT and 0.91 on sCT. According to the result of dose calculation, we found when the bladder volume underwent a substantial change (79.7%), the bladder dose is still within the safe limit, suggesting it is insufficient to solely use the bladder volume change as a criterion to determine whether adaptive treatment needs to be done. After AD-contours of the bladder using sCT, there are two cases whose bladder dose . For the two cases, we perform re-planning to reduce the bladder dose to , under the condition that the PTV meets the prescribed dose.
We provide a dose accurate adaptive workflow for prostate cancer patients by using deep learning approaches, and implement ART that adapts to bladder dose. Of note, the specific replanning criterion for whether ART needs to be performed can adapt to different centers' choices based on their experience and daily observations.
自适应放疗（ART）可在分次放疗的重新优化治疗计划中纳入解剖学变异。非常需要一种自动解决方案，以客观地确定在每日图像采集后是否应立即进行ART。
我们通过合成伪CT（sCT）图像并使用深度学习方法评估对治疗计划的剂量学影响，来研究前列腺癌放疗中是否应进行ART的定量标准。
使用74例患者的计划CT（pCT）和每日锥形束CT（CBCT）数据集来训练（60例患者）和评估（14例患者）一个循环对抗生成网络（CycleGAN），该网络执行从每日CBCT合成高质量sCT的任务。使用U-net在sCT上对膀胱进行自动勾画（AD）。sCT和AD的结合使我们能够根据最新的膀胱解剖结构进行剂量计算，以确定原始治疗计划（ori-plan）是否仍然适用。对于患者解剖结构变化和相关剂量计算需要重新规划的阳性病例，我们基于ori-plan进行快速计划修订（re-plan）。
sCT和pCT之间感兴趣区域（即身体、膀胱、脂肪、肌肉）内的平均绝对误差分别为41.2、25.1、26.5和29.0HU。以pCT剂量的计算结果为标准，对于计划靶体积（PTV），sCT剂量在1mm/1%、2mm/2%时的伽马通过率分别为87.92%、98.78%。AD轮廓在pCT上的骰子系数为0.93，在sCT上为0.91。根据剂量计算结果，我们发现当膀胱体积发生显著变化（79.7%）时，膀胱剂量仍在安全范围内，这表明仅以膀胱体积变化作为确定是否需要进行适应性治疗的标准是不够的。使用sCT对膀胱进行AD轮廓勾画后，有两例患者的膀胱剂量……对于这两例患者，我们进行重新规划，在PTV满足规定剂量的条件下，将膀胱剂量降低到……
我们通过使用深度学习方法为前列腺癌患者提供了一种剂量准确的自适应工作流程，并实施了适应膀胱剂量的ART。值得注意的是，是否需要进行ART的具体重新规划标准可根据不同中心的经验和日常观察进行调整。
